Enterprise networks are carrying a very fast growing volume of both business and non-business critical traffics. Often, business applications such as video collaboration, cloud applications, etc., use the same hypertext transfer protocol (HTTP) and/or HTTP secure (HTTPS) techniques that are used by non-business critical web traffic. This complicates the task of optimizing network performance for specific applications, as many applications use the same protocols, thus making it difficult to distinguish and select traffic flows for optimization.
As the number of business and non-business critical applications increases, so too are the number and variety of service level agreements (SLAs) that may be in use by a network. In general, an SLA refers to a target or threshold level of performance guaranteed by the network, and may be associated with a particular type of traffic. For example, many real-time business applications are very bandwidth demanding and having corresponding SLAs that are used to ensure that a certain amount of network bandwidth is available for a particular flow of traffic.
Traditionally, reactive techniques have been used to enforce network performance criteria, such as SLAs. First, the network itself is engineered by defining the application SLAs, quality of service (QoS) parameters, security settings, etc. Next, the performance criteria are monitored in view of the network's performance. If the performance criteria are not met, adjustments may then be made to the network in a reactive manner. Many networking mechanisms exist today to provide on-the-fly guaranteed network performance, such as call admission control, resource reservation, queuing, traffic shaping, etc. However, these tools require careful engineering to perform highly complex tasks in terms of traffic classification, QoS, routing, network and application SLA monitoring, etc. in view of the highly dynamic nature of the traffic and the network. All combined, these techniques make the configuration of a network extremely complicated, while still relying on the fundamental paradigm of reactive networking.